Global Co-Evolution of Carbon Pricing Instruments, Emissions Coverage and Revenues: A Long-Run Time-Series Assessment
炭素価格制度、排出カバー率、収入のグローバルな共進化：長期時系列分析 (AI 翻訳)
Mariusz Pyra
🤖 gxceed AI 要約
日本語
本稿は1990～2024年の炭素税・排出量取引制度の普及、カバー率、収入の長期時系列データを用いて、3指標の共進化パターンを分析。相関分析・トレンドモデルにより、制度数と排出カバー率に強い正の相関を確認し、収入は非線形的に拡大することを示した。因果推論には慎重であり、今後のパネルデータ分析の必要性を指摘。
English
This paper analyzes the long-run co-evolution of carbon pricing mechanisms, emissions coverage, and revenues using annual global time-series data (1990-2024). It finds a robust positive correlation between the number of mechanisms and coverage, and nonlinear revenue growth. The study offers a transparent empirical synthesis while explicitly noting limits to causal inference.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本では2023年にGXリーグ/CAS本格稼働、2024年から排出量取引制度の試行開始。本稿は世界全体の炭素価格制度の実証的傾向を示すことで、日本の制度設計や国際動向のベンチマークとして活用できる。
In the global GX context
As ISSB, CSRD, and SEC climate rules push for carbon pricing disclosure, this paper provides a credible empirical baseline on global carbon pricing diffusion, coverage, and revenue trends. It supports policymakers and investors in assessing market maturity and fiscal potential.
👥 読者別の含意
🔬研究者:Provides a transparent, replicable methodology for analyzing carbon pricing diffusion and revenue scaling, with clear future research directions.
🏢実務担当者:Useful for benchmarking corporate carbon pricing exposure and understanding global coverage trends for risk assessment.
🏛政策担当者:Offers empirical evidence on the long-term relationship between carbon pricing instrument count, emissions coverage, and revenue growth.
📄 Abstract（原文）
The expansion of carbon pricing instruments, such as carbon taxes and emissions trading systems (ETS), has been rapid over the last three decades. However, the global quantitative evidence is often presented in descriptive reports rather than in a unified empirical framework. The present study documents the long-run co-evolution between three factors: firstly, the global diffusion of carbon pricing mechanisms, secondly, the share of global greenhouse gas emissions covered by an explicit carbon price, and thirdly, global carbon-pricing revenues. The present study utilises annual global time-series data spanning the period 1990–2024 (mechanisms) and overlapping samples for coverage and revenues (2005–2024; 2006–2023). Employing correlation analysis, trend modelling and robustness checks tailored to trending series, the study offers a transparent and replicable quantitative synthesis of the data. The findings suggest a robust positive long-term correlation between the number of mechanisms in operation and emissions coverage. Revenues manifest a pronounced non-linear scaling over time; nevertheless, given the aggregate nature of the dataset, the estimates are interpreted as co-movement patterns rather than causal effects of specific instruments. The paper makes a significant contribution to the field by offering a transparent and replicable quantitative synthesis of global carbon-pricing diffusion and fiscal scaling. It is important to note, however, that the paper also explicitly states the limits of causal inference and outlines panel-data extensions for future research.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.3390/en19051277first seen 2026-05-05 22:41:53
gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。